Publications

AACR 2024

Spatially resolved cell profiling unveils tumor metabolic statesassociated with immunotherapy response in NSCLC

AACR 2024

Next Generation H&E Cell Modeling: Leveraging Multiplex Imaging to Create Large-Scale H&E Cell Annotations For Deep Learning

SITC 2023

Enhancing insights in low-plex multiplex immunofluorescence leveraging the potential of same-slide H&E analysis

SITC 2023

Unveiling the diversity of Melanoma immunotherapy response biomarkers between Lymph node and non-lymph node biopsies

ESMO 2023

Utilizing H&E Images and Digital Pathology to Predict Response to Buparlisib in SCCHN

AACR 2023

Identification of tertiary lymphoid structures from H&E slides using deep learning analysis of nuclear morphology is associated with favorable survival in colorectal cancer patients

USCAP 2023

Deep Learning-Based Evaluation of PD-L1 Immunohistochemistry-Stained Slides for Robust Tumor Proportion Scoring Enables Better Categorization of Non-Small-Cell Lung Cancer Cases

BioRxiv

A novel deep learning pipeline for cell typing and phenotypic marker quantification in multiplex imaging

SITC 2022

Predicting response to immune checkpoint inhibitors (ICI) in non-small-cell lung cancer (NSCLC) by combining spatial analysis of cells and RNA sequencing data from biopsies using deep learning (DL)

SITC 2022

Predicting CD8+ cell density and tumor-immune phenotypes in non-small-cell lung cancer (NSCLC) from standard H&E slides using deep learning (DL)

SITC 2022

A deep learning analysis pipeline for multiplex imaging identifies spatial features associated with clinical outcome in colorectal cancer

ENA 2022

Predicting response to naratuximab emtansine, an anti-CD37 antibody-drug conjugate (ADC), in combination with rituximab in Diffuse Large B Cell Lymphoma (DLBCL), by analyzing the spatial arrangement of CD37 and CD20 positive cells using deep learning

Pathology Visions 2022

Generating Virtual Multiplex Images from Sequential Immunohistochemistry (IHC) Slides using Deep Learning

ESMO 2022

Predicting response to pembrolizumab in non-small cell lung cancer using spatial analysis of biopsy images by deep learning

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